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ISSN 印刷: 2152-5080
ISSN オンライン: 2152-5099

近刊の記事

Learning a class of stochastic differential equations via numerics-informed Bayesian denoising Zhanpeng Wang, Lijin Wang, Yanzhao Cao

Zhanpeng Wang
University of Chinese Academy of Sciences

Lijin Wang
University of Chinese Academy of Sciences

Yanzhao Cao
Auburn University

DOI: 10.1615/Int.J.UncertaintyQuantification.2024052020

Covariance estimation using h-statistics in Monte Carlo and multilevel Monte Carlo methods Sharana Kumar Shivanand

Sharana Kumar Shivanand
The Alan Turing Institute

DOI: 10.1615/Int.J.UncertaintyQuantification.2024051528

Bayesian Parameter Inference for Partially Observed Diffusions using Multilevel Stochastic Runge-Kutta Methods Pierre Del Moral, Shulan Hu , Ajay Jasra, Hamza Ruzayqat, Xinyu Wang

Pierre Del Moral
Institut de Mathematiques de Bordeaux

Shulan Hu
Zhongnan University of Economics and Law

Ajay Jasra
The Chinese University of Hong Kong, Shenzhen

Hamza Ruzayqat
King Abdullah University of Science and Technology

Xinyu Wang
Zhongnan University of Economics and Law

DOI: 10.1615/Int.J.UncertaintyQuantification.2024051131

Derivative-based Shapley value for global sensitivity analysis and machine learning explainability Hui Duan, Giray Okten

Hui Duan
Florida State University

Giray Okten
Florida State University

DOI: 10.1615/Int.J.UncertaintyQuantification.2024051548

Maximizing Regional Sensitivity Analysis indices to find sensitive model behaviors Sebastien Roux, Patrice Loisel, Samuel Buis

Sebastien Roux
INRAE

Patrice Loisel
INRAE

Samuel Buis
INRAE

DOI: 10.1615/Int.J.UncertaintyQuantification.2024051424

Measuring inputs-outputs association for time-depending hazard models under safety objectives using kernels Matieyendou LAMBONI

Matieyendou LAMBONI
University of Guyane

DOI: 10.1615/Int.J.UncertaintyQuantification.2024049119

Application of global sensitivity analysis for identification of probabilistic design spaces Sergei Kucherenko, Dimitris Giamalakis, Nilay Shah

Sergei Kucherenko
Imperial College London

Dimitris Giamalakis
Imperial College London

Nilay Shah
Imperial College London

DOI: 10.1615/Int.J.UncertaintyQuantification.2024051384

SENSITIVITY ANALYSES OF A MULTI-PHYSICS LONG-TERM CLOGGING MODEL FOR STEAM GENERATORS Edgar Jaber, Vincent Chabridon, Emmanuel Remy, Michaël Baudin, Didier Lucor, Mathilde Mougeot, Bertrand Iooss

Edgar Jaber
EDF R&D, Centre Borelli, LISN

Vincent Chabridon
EDF R&D

Emmanuel Remy
EDF R&D

Michaël Baudin
EDF R&D

Didier Lucor
LISN, UPSaclay

Mathilde Mougeot
Centre Borelli, ENS Paris-Saclay

Bertrand Iooss
Institut de Mathématiques de Toulouse, 31062 Toulouse, France; EDF Lab Chatou, 78401 Chatou, France

DOI: 10.1615/Int.J.UncertaintyQuantification.2024051489

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